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Analysis of In-Space Assembly of Modular Systems 



Robert W. Moses*, James Van Laak^, Spencer L. Johnson*, Trina M. Chytka^, 

Ruth M. Amundsen**, John T. Dorsey**, Wilham R. Doggett** 

NASA Langley Research Center, Hampton, VA 23681 

John D. Reeves^^ 
National Institute of Aerospace, Hampton, VA 23666 

B. Keith Todd*** 
NASA Johnson Space Center, Houston, TX 77058 

Damon B. Stambohan*** 
NASA Kennedy Space Center, KSC, FL 32899 

and 

Rud V. Moe*** 
NASA Goddard Space Flight Center, Greenbelt, MD 20771 



Early system-level life cycle assessments facilitate cost effective optimization of system 
architectures to enable implementation of both modularity and in-space assembly, two key 
Exploration Systems Research & Technology (ESR&T) Strategic Challenges. Experiences 
with the International Space Station (ISS) demonstrate that the absence of this rigorous 
analysis can result in increased cost and operational risk. An effort is underway, called 
Analysis of In-Space Assembly of Modular Systems, to produce an innovative analytical 
methodology, including an evolved analysis toolset and proven processes in a collaborative 
engineering environment, to support the design and evaluation of proposed concepts. The 
unique aspect of this work is that it will produce the toolset, techniques and initial products 
to analyze and compare the detailed, life cycle costs and performance of different 
implementations of modularity for in-space assembly. A multi-Center team consisting of 
experienced personnel from the Langley Research Center, Johnson Space Center, Kennedy 
Space Center, and the Goddard Space Flight Center has been formed to bring their 
resources and experience to this development. At the end of this 30-month effort, the toolset 
will be ready to support the Exploration Program with an integrated assessment strategy 
that embodies all life-cycle aspects of the mission from design and manufacturing through 
operations to enable early and timely selection of an optimum solution among many 
competing alternatives. Already there are many different designs for crewed missions to the 
Moon that present competing views of modularity requiring some in-space assembly. The 
purpose of this paper is to highlight the approach for scoring competing designs. 



* Principal Investigator, Exploration Systems Engineering Branch, MS 472, AIAA Associate Fellow. 
^ Head, Systems Management Office, MS 165. 

* Project Manager, Mechanical Systems Branch, Systems Engineering Directorate, MS 468. 

^ Operations & Mission Requirements, Exploration Concepts Branch, MS 365, AIAA Member. 

** Aerospace Engineer, Structural and Thermal Systems Branch, MS 431, AIAA Member. 

^^ Senior Research Engineer, Metals and Thermal Structures Branch, MS 396, AIAA Associate Fellow. 

** Senior Research Engineer, Guidance & Controls Branch, Research & Technology Directorate, MS 161. 

^^ Research Engineer, Research Staff, MS 451, AIAA Member. 

*** Robotics and Crew Systems Operations Division, Code DXl, AIAA Senior Member. 

^^^ Human Factors Engineering, Exploration Operations Integrations, Code UB-X. 

*** Senior Research Engineer, Hubble Space Telescope Development Project, Code 442. 

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I. Introduction 

EARLY system-level life cycle assessments facilitate optimization of system architectures to achieve a cost- 
effective approach to both modularity and in-space assembly, two key Exploration Systems Research & 
Technology (ESR&T) Strategic Challenges. Experiences with the International Space Station (ISS) demonstrate that 
the absence of this rigorous analysis can result in increased cost and operational risk. The ability to assess those 
costs and risks driven by modularity and in-space assembly must be available for design selection. Already, different 
designs for the Crew Exploration Vehicle (CEV) present competing views of modularity requiring some in-space 
assembly \ However, the ability to analyze the many options for comparison in terms of life cycle cost and risk is 
not available presently. 

Analyzing modularity and in-space assembly to assess their impact on mission architecture poses many 
challenges. For Apollo, a heavy lift launch capability permitted minimal modularity and in-space assembly. That 
launch capability no longer exists; even if it did, the high degree of human presence envisioned by NASA for the 
Moon will require far more resources delivered to the surface of the Moon than ever before. Furthermore, placing 
humans safely on Mars and bringing them safely home pose orders of magnitude more difficulty than previous space 
accomplishments stemming from Mercury through ISS. 

An affordable, sustainable exploration program to Mars and beyond will require technologies that deviate from 
heritage hardware. Thus, models and analysis will require updating to factor those new technologies into mission 
architecture. Thus, any analysis approach must be flexible and contain elements that are reliably employed and their 
results easily understood. 

II. Purpose and Expectations 

The Analysis of In- Space Assembly of Modular Systems effort will produce an analytical methodology to 
support the design and evaluation of proposed exploration architectures. The methodology will include an evolved 
analysis toolset and proven processes brought together in a collaborative engineering environment. The toolset, 
techniques, and initial products will be used to analyze and compare the detailed, life cycle costs and performance of 
different implementations of modularity for in-space assembly within competing mission architectures, including 
system design and manufacturing, sustaining engineering, the design robustness for flight operations and consequent 
requirements for real-time engineering support, crew and flight controller training, and logistics supportability. The 
tools will provide insight into how the various implementations of modularity affect vehicle mass, power and 
thermal rejection capability, and vehicle safety through safe haven and other inherent characteristics. Since the 
combined effects of these implementation decisions can have major impacts on system effectiveness, cost and 
supportability, this work will provide tools and initial analyses to identify design discriminators and establish the 
appropriate level of modularity to be sought in the design of Exploration hardware. 

A multi-Center team from the Langley Research Center, Johnson Space Center, Kennedy Space Center, and the 
Goddard Space Flight Center will bring their resources and experience to bear on this work. Leadership and 
management will be provided by the Langley team, which offers a rich blend of comprehensive systems analysis 
capability together with a highly experienced systems engineering organization, thus providing technical capability 
from concept development to design solutions. JSC will provide their extensive expertise in human and robotic 
extra-vehicular activity, as well as critical operations analysis of system strengths and weaknesses during real-world 
assembly operations and extended mission operations. KSC will analyze pre-flight processing of modular elements 
and offer insight into techniques and opportunities for integrated testing prior to launch. GSFC will support the 
analysis with their expertise on maintenance and repair of the modular systems in flight. 

At the end of this 30-month effort, the toolset will be ready to support the Exploration Program with an 
integrated assessment strategy that embodies all life-cycle aspects of the mission from design and manufacturing 
through operations to permit early and timely selection of an optimum solution among many competing alternatives. 
The purpose of this paper is to highlight the approach for scoring competing designs. 

III. Analysis Approach and Focus 

The analysis approach consists of several tasks. First, requirements will be assembled, and evaluation criteria; 
second, the ensemble of the experts in a collaborative engineering environment to employ analysis tools and intellect 
for applying the requirements and evaluation criteria. The criteria are applied to the design reference mission from a 
separate mission architecture study by NASA, and then scoring the competing designs that claim to enable NASA's 
exploration vision. The streamlining of this analysis capability is also to support simulation based acquisition (SBA). 

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This 30-month effort will focus on two key issues: 1) the combined system of systems implications of modular 
designs and their assembly in space; and 2) the interfaces between modules and their impact on the assembly and 
detachment phases near Earth and the target destination. 

A. Requirements and Evaluation Criteria 

The requirements and evaluation criteria for scoring competing approaches to modularity requiring in-space 
assembly will include many elements of traditional systems engineering. Life cycle cost will factor strongly in the 
scoring of competing designs. 

The project will include discipline specialists in launch processing from Kennedy Space Center, in-space 
assembly from Johnson Space Center, and on-orbit servicing from Goddard Space Flight Center. Launch processing 
requirements include those affecting payload launch preparation, payload launch pad scenarios and sequences, and 
payload start-up and initial check-out. In-space assembly requires astronaut assembly operations, training, practices, 
and tools along with interfaces, attachments, mechanisms, and positioning guides. On-orbit servicing also focuses on 
astronaut workloads and support logistics. 

Some additional requirements by the Exploration Systems Mission Directorate are expected to be levied on this 
project as other projects mature. The NASA-directed requirements will affect the implementation and operations of 
the analysis capability planned for the Integrated Design Center (IDC) at the Langley Research Center (Figure 1). 
Working with other integrated design centers in the agency, the IDC tools and operations will provide access to the 
analysis capabilities for teams supporting coast-to-coast operations as part of NASA's ASCT (Advanced Studies, 
Concepts, and Tools) Advanced Studies. These requirements may dictate additional software and hardware 
capabilities for the IDC that would not otherwise be required if all experts were residing in one room. In addition, 
this project has the responsibility for non-robotic interfaces and their standards because they may impact the design 
reference architecture. This project will study the heritage and proposed physical interfaces between modules and 
assess their implications on the life cycle cost of future exploration hardware systems. Furthermore, the analysis 
capabilities developed for this project may be modified later to accommodate specific requirements on SB A. 



U Requirements Documents 
U Evaluation Criteria Document 
U Impact of Non-Robotic Interfaces 
on selected Mission Architectures 




Figure 1. The IDC provides a single design path, simpHfies user operations and logistics, and provides for 

communication among disciplines. 



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B. Analysis Capability and Planned Tools 

The purpose of this effort is to develop the tools and the approach to properly analyze the benefits and costs of 
implementing modularity in a space flight system. The product is the capability to generate a global optimization of 
the integrated system performance across the entire life cycle of the Exploration Program, with emphasis on the 
reliability and sustainability parameters that define the most critical performance requirements of exploration 
systems. Because many disciplines and experiences in space flight across the agency will be required, the best forum 
for bringing these resources together appears to be a collaborative engineering environment. This type of forum has 
been implemented successfully for spacecraft missions at JPL and GSFC. The IDC at LaRC provides a similar 
collaborative forum but with emphasis on systems analysis and systems engineering capabilities (Figure 2). The 
software tools currently in use at the IDC include commercially available 3-D physics-based simulations. For 
instance, the IDC has the capability to analyze in-space assembly by combining computer-aided design (CAD) 
models of modular hardware geometry with multi-satellite trajectory analysis software. At times, new software or 
hardware tools are incorporated to allow for inclusion of other capabilities into the collaborative engineering 
environment. As other partners join in the IDC, their software tools will be incorporated into the rich toolset. The 
tools for this effort currently exist but as components residing at separate locations. They will be integrated into a 
collaborative engineering toolset and validated against a relevant case. 




Figure 2. Multiple perspectives of results of a study conducted within the IDC at LaRC provide early insight 

into design drivers. 

Two tools currently in the plans to acquire for the IDC are teleconferencing with other collaborative design 
centers at JPL and GSFC and discrete event simulation (DES) with integrated life cycle cost features. The former 
tool will use commercially available items that will require little to no modification to implement within the IDC. 
For the latter, DES is a numerical computer-based analysis technique that models discrete changes in the state of the 
system in order to capture the dynamics between various entities and events. DES is a methodology that has gained 
popularity in the aerospace field due to its ability to dynamically model complex logistical flow paths such as launch 
vehicle ground preparation operations. A properly developed DES model is capable of capturing a wide variety of 
model characteristics such as life cycle costs and aggregate vehicle reliabilities. The essence of DES is that it is used 
to probabilistically study model input assumptions and resulting output metrics in order to better capture real-world 
uncertainty and variability. One popular commercial DES tool used extensively at Langley Research Center will be 
added to the IDC when needed by the team during focused activities. An example of the capabilities of DES will be 
illustrated later in this paper to underscore its importance to this project. 

C. DES and the Analysis of In-Space Assembly of Modular Systems 

The analytical methodology to be developed during this effort includes an evolved analysis toolset that captures 
all of the disciplines necessary to evaluate proposed concepts. The first phase of the project will determine the 
disciplines and tools needed to support the analysis. The various discipline tools will be identified and integrated 
into Langley' s IDC, and data standards will be established to ensure that the tools generate results in a standard form 
(e.g.. Standard International units). The collaborative environment may utilize an automated interface or subject 
matter experts may act as intermediaries between the tools and the rest of the design team. A central tool will bring 



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together the output data from the disciphne tools in order to generate hfe cycle scoring. A DES life cycle analysis 
model, in conjunction with some supporting software such as a spreadsheet utility with embedded macro programs, 
will facilitate this type of analysis by capturing all of the interactions that take place during a mission cycle such as 
ground operations, schedule delays, on-orbit assembly operations, and logistical operations beyond LEO. 
Standardized outputs from the various discipline tools can be brought into the DES model either deterministically or 
probabilistically to allow evaluation of the scenario and to generate an overall scoring metric or set of metrics. 
Sensitivity analyses will be performed on the various inputs in order to understand which parameters drive life cycle 
costs. Sensitivity analysis capability would allow decision makers to see if slight changes in proposed designs could 
influence which proposal is superior, and thus yield a more robust decision. 

NASA has recently begun looking into various ways to implement SBA, an acquisition philosophy that utilizes 
computer-based simulation techniques to make procurement decisions. DES as a component for the Analysis of In- 
Space Assembly of Modular Systems project will enhance the Agency's SBA capabilities. 

D. Existing DES Model for On-Orbit Assembly Analysis 

The current model, designated the Architectural Model, was initially developed to analyze life cycle costs for 
launch vehicle ground operations for a variety of existing and proposed vehicle concepts, both reusable and 
expendable. This original model was a high-level simulator of all critical activities that are involved with preparing 
and recovering from a launch, such as processing reusable components, acquiring expendable components, 
integration in a dedicated integration facility, launch operations, and recovery and safing activities. The model was 
later amended to capture on-orbit assembly operations in low earth orbit in order to study modularity impacts of a 
sample manned lunar mission. Because of this, the model is in line with what the Analysis of In-Space Assembly of 
Modular Systems effort is trying to accomplish in terms of studying the particulars that go into assembling modular 
systems on orbit. Added fidelity and a broadening of scope of the Architectural Model will be required during the 
study in order for the model to act as the life cycle scoring tool for the overall analysis methodology. 



Loiters in LO 



Lunar 
Orbit 



— ^^eT^- 



. Lunar 
.Surface 



7 day surface stay 



Dump AS, 
restackwith TEI 



/ 



AsbM) D TEI 



3 day 



407 km orbit 

Earth 
Orbit 



^9 



p TEI e^^omIas sh ds 

I 



TLI2 



TLIl d 



N 



LEGEND : 

Ascent Stage (AS) 

Entry Vehicle (EV) = Crew stay, hrs 

Descent Stage (DS) 

Surface Habitat (SH) = 7 day 

Orbital Module (OM) = 2-3 day habitat 

Trans-Earth Injection (TEI) stage 

Trans-Lunar Injection (TLI) stage 



3 day 




Dump TEI, OM, 
crew entry in EV 



- Earth 
■Surface 



Figure 3. Example reference lunar mission system study showing eight modules with 

assembly in Earth and Lunar orbits. 

Since the Architectural Model is a top-level analysis tool, various assumptions were made during development in 
order to narrow the scope of what was being analyzed. For example, the model focuses on one lunar mission at a 
time, with the definition of a lunar mission consisting of one assembled vehicle being sent on a trans-lunar trajectory 



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(figure 3). The model generates both cost and mission success metrics, with cost incorporating just the launch costs 
associated with the operation of various launch vehicles, and the success metrics being related to successfully 
getting the modules integrated on orbit and sent on a trans-lunar trajectory before orbit degradation effects become 
significant (figure 4). Any number of Earth-to-orbit launches can be used in order to deliver vehicle modules to 
LEO. Each vehicle module delivered to orbit has an associated corresponding automated rendezvous and docking 
(AR&D) reliability that allows parametric analysis of the impacts of docking failures. Any sort of docking failure or 
other failure that prevents a particular vehicle module from integrating with the rest of the modules results in a 
relaunch, which inherently incurs additional launch costs (figure 5). Any sort of launch vehicle concept can be 
loaded into the model since there are mechanisms that allow both reusable and expendable process flows to be 
captured. The model is also capable of capturing launch vehicle costs on either a facility-use basis or a contractual 
fixed cost per launch. 

The Architectural Model is manifest-driven, meaning a launch schedule has to be fed into the model that 
contains specifics such as target launch dates and payload assignments. There are also two tiers of decision gates 
embedded in the model, both of which contribute to the resulting cost and success metrics. The upper tier is a lunar 
mission specific tier that relates to the following: timely ground processing for all launches, successful integration of 
all modules, and whether or not the assembled vehicle is sent on a trans-lunar trajectory before orbit degradation 
effects become significant. The second tier of decision points pertains to the individual launches that are specified 
on the manifest. These decision points include loss of vehicle scenarios during launch, payload delivery failures 
(payload cannot reach correct orbit), and failure of individual payload modules to integrate. The model is currently 
set up with no animation features in order to facilitate the rapid execution of a multiple replication run. Visual Basic 
for Applications (VBA) coding is used via a spreadsheet database tool to load various manifests into the model, 
execute the model, and to retrieve and tabulate the resulting output metrics in an automated fashion. Because this 
spreadsheet database tool allows a user to automatically run any number of manifests serially through the model, it 
lends itself to Design of Experiment (DoE) studies regarding the manifest inputs. 



Operational Scenario 



LEGEND : 

Ascent Stage (AS) 

Descent Stage (DS) 

Entry Vehicle (EV) = Crew stay, 2-3 day 

Orbital Module (OM) = 2-3 day habitat 

Surface Habitat (SH) = 7 day 

Trans-Earth Injection (TEI) stage 

Trans-Lunar Injection (TLI) stage 




• All missions must be scheduled, processed and 
launched to meet degradation window requirements 

• Include metrics for 

• LOV - Loss of Vehicle 

• PDF - Payload Delivery Failure; failure to 
properly deliver payload 

• Failure of either initiates a re-launch 



• Trans-lunar injection initiated 

at next available lunar launch 
window. 

• MS - Mission Success; 
success of integrated on-orbit 
launch to lunar orbit 




This window requires full integration 
and launch prior to orbit degradation 
threshold 

FT! - Failure to Integrate (on-orbit); 
AR&D success rate 



Mission Launch Window 



Figure 4. Operational scenario for example reference lunar mission system study. 



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Architecture Costs Averaged 



40 
35 



£ 30 
^ 25 
S3 20 
"5 15 

(0 

o 10 



Manifest assumptions based on 
logical mass packaging and series 
of launches and in-space assemblies 




-4 
-5 
-6 
7 
-8 
-9 
-10 
-11 



100 95 90 85 

AR&D Reliability (%) 



80 



Figure 5. Cost differential for selected cases of modularity having a range of AR&D 
reliability for the example reference lunar mission study. 

E. Future Development of DES Model 

Although the Architectural Model captures many of the various logistical operations that need to be analyzed in 
order to score overall life cycle costs, the model's scope will be expanded in order to address all aspects needed for 
the Analysis of In- Space Assembly of Modular Systems study. The model currently only simulates operations up 
through the trans-lunar injection burn, but will need to also simulate trans-lunar operations and transit times, lunar 
orbit operations, descent operations, surface habitation operations, ascent operations, as well as the logistics 
involved with returning back to earth. Since the current model only captures launch costs, the various vehicle 
module costs and mission support costs will also be incorporated. A higher level of fidelity will have to be added to 
the modeling of on-orbit assembly operations since this is the focal point of the study and the model currently only 
treats this as a single decision point per module. The distinction being made between robotic and non-robotic 
interface and assembly operations will be incorporated into this model logic. 

The output metrics of the model will be revisited and refined in order to generate metrics that are specific to this 
study. A scoring function will be generated by the team that takes into account various output parameters from the 
DES model as well as some from the other discipline tools, which will require that the model be modified to 
generate the needed metrics. 

F. Model Verification and Validation 

In order for any numerical simulation model to be considered credible, some sort of verification and validation 
(V&V) methodology is needed (when possible) to ensure that a) the model is correctly coded (verification) and b) 
the model is modeling the system appropriately (validation). Such "sanity checks" against the model can be 
accomplished using a wide range of techniques, some quantitative and some qualitative. A particular obstacle that 
has plagued the application of DES in conceptual design in the space industry is lack of historical numerical data 
that can be used to corroborate model output data. Current mission objectives pose challenges of going to the Moon 
that exceed the scope of Apollo, and going to Mars has no known analog. The only analog that comes close to 
NASA's current exploration goals is the ISS. Because of this, V&V ends up taking more qualitative forms and relies 
heavily on expert opinion. 

During this study, heavy emphases will be placed on the application of V&V techniques whenever appropriate to 
establish "confidence" in the resulting output data. There are many different definitions and listings of various V&V 
techniques that can be used to substantiate computer models. One source^ in particular lists fourteen different V&V 



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techniques, eight of which can be applied in the case where there is no real-world data to use for corroboration. The 
eight applicable techniques are as follows: 
i.Animation - graphical representation of entity flow throughout the model 

ii.Comparison to Other Models - comparison to other life cycle analysis tools in the industry 

iii. Degenerate Tests - sanity checks of specific pieces of coding logic 

iv.Extreme Condition Tests - analysis of output data resulting from extreme combinations of inputs 

v.Face Validity - subject matter expert corroboration of model behavior 

vi .Internal Validity - analysis of internal model variability to ensure that model is consistent 
vii.Operational Graphics - various performance measures displayed graphically such as queue lengths 
viii.Traces - specific entities traced throughout the model to ensure proper logic flow 

In addition to these qualitative measures, subject matter experts will analyze all input data and data distributions 
in order to ensure credible model runs. Part of the purpose of the IDC is to involve discipline experts to allow proper 
quality control of data being passed between analysis tools. Although it may not be possible to statistically verify 
and validate computer models of future space operations, particularly one that deals with the on-orbit assembly of 
modular systems, credibility will be established by SME (Subject Matter Experts) approval of input data in 
conjunction with the eight qualitative techniques mentioned. 

IV. Life Cycle Cost Analysis 

Life Cycle Cost (LCC) analysis is a collective term comprising many kinds of analysis, e.g., reliability- 
availability-maintainability (RAM) analysis, economic analysis, risk analysis, etc. A main objective of the LCC 
analysis is to quantify the total cost of ownership of a system throughout its full life cycle, which includes research 
and development, production, operation and maintenance, and disposal. The predicted LCC is useful information for 
decision making in acquisition strategies, optimizing designs, developing logistics (maintenance) philosophies, or in 
multi-alternative selections. The Analysis of In-Space Assembly of Modular Systems effort will use LCC analysis as 
a first line discriminator for underscoring the advantages and disadvantages of competing modularity architectures. 

The act of in-space assembly may not necessarily impact the costs in the other areas, shown in Table 1. 
However, the choices made in those other areas may have strong implications for the costs of launch processing and 
in-space assembly. For example, as demonstrated above, the number of modules has little impact on the total launch 
cost for placing those modules in orbit. The reason that launch cost is relatively insensitive to modularity is that the 
total space exploration system can be cleverly broken down to fit within a variety of launch vehicles having 
favorable costs. However, breaking the spacecraft into many modules to optimize launch cost may have severe 
consequences for the costs for in-space assembly, if reliability is affected. For instance, if the spacecraft is broken 
into 20 launches and the reliability of the selected in-space assembly method is 1 in 20 (0.95), then the chance of 
losing one module is "statistically probable". As a result, in the analysis, one (unlucky) module will be lost, and the 
impact of losing that module will reverberate throughout the entire system of systems and its life cycle. In the 
analysis, each module will take its turn at being lost, and the sensitivity of the system to its loss will be calculated. 
Furthermore, if the unlucky module involves the loss of an astronaut, then the costs due to an extensive accident 
investigation, including an "indefinite" safety stand-down, can be too great for the program to bear. Thus, in-space 
assembly is highly sensitive to decisions made in other areas. Therefore, requirements for in-space assembly must be 
fed upstream (to the left in Table 1) so to minimize the likelihood of a "statically probable" and costly incident. 



Table 1. Areas of Life Cycle Cost Important to In-Space Assembly of Modular Systems 



Systems 


Systems design 


Flight 


Launch 


Mission 


System 


requirements 


& manufacturing 


certification & 


processing & 


insertion & 


retirement 


development 


(modularity 


launch 


in-space 


mission 






selection) 


selection 


assembly 

(operations) 


operations 

(system of 

systems) 





One overarching constraint to estimating life cycle costs is that one cost modeling technique may not apply to all 
areas. For instance, cost modeling techniques that are highly sensitive to payload mass may not work well for areas 
involving an extensive software development and test demonstration project. Software has no mass, yet the cost to 
develop it can consume the largest part of a project budget. Thus, some care must be given to the selection and 
sensitivities of the cost modeling used in all areas. Furthermore, some resources may be required to seam the 
different cost models into one life cycle model. These factors will be explored further for developing the most 



8 
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comprehensive yet seamless life cycle costing model possible within the scope of this project. Some guidance is 
expected from the SBA group during development. 

V. Conclusion 

Current architecture studies illustrate some effects of modularity and the underlying AR&D reliability on the 
launch phase of mission life cycle costs. The main goal of Analysis of In-Space Assembly of Modular Systems is to 
build upon those studies to score competing approaches to assembling and detaching those modules during the entire 
operational scenario. This project has identified the core experts and fundamental tools necessary to meet that main 
goal and strives to implement them within a collaborative engineering environment for increased productivity. Once 
operational, this analysis capability will work in concert with other Advanced Concepts projects and SBA activities 
to build a coast-to-coast analysis support infrastructure for ESR&T. 

Acronyms 

AR&D Autonomous Rendezvous and Docking 

ASCT Advanced Studies, Concepts, and Tools 

CEV Crew Exploration Vehicle 

DES Discrete Event Simulation 

DoE Design of Experiments 

ESR&T Exploration Systems Research and Technology 

GSFC Goddard Space Fhght Center 

IDC Integrated Design Center 

ISS International Space Station 

JSC Johnson Space Center 

KSC Kennedy Space Center 

LaRC Langley Research Center 

LEO Low Earth Orbit 

LCC Life Cycle Cost 

RAM Reliability- Availability-Maintainability 

SBA Simulation Based Acquisition 

VBA Visual Basic for Applications 

V&V Verification and Validation 

Acknowledgments 

The authors would like to express their gratitude to the many former and present contributors and co-workers 
among the NASA Centers and participating organizations for a rich heritage from which to build NASA's next 
exploration missions. Their remarkable successes inspire us to reach new heights through difficult challenges. 

References 

^Sietzen, P., Jr., "From Columbia to Constellation: Crafting a New Space Policy," Aerospace America, Vol. 42, 
No. 4, April 2004, pp. 36-43. 

^Sargent, R. G., "Verification and Validation of Simulation Models," Proceedings of the 2003 Winter Simulation 
Conference, IEEE, New Orleans, LA, 2003, pp. 41. 



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